QoE-Driven DASH Video Caching and Adaptation at 5G Mobile Edge
QoE-Driven DASH Video Caching and Adaptation at 5G Mobile Edge
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DOI：
10.1145/2984356.2988522
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发表时间：
2016-09
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影响因子：
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通讯作者：
Chang Ge;Ning Wang;Severin Skillman;G. Foster;Yue Cao
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文献类型：
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作者：
Chang Ge;Ning Wang;Severin Skillman;G. Foster;Yue Cao
在本文中，我们提出了一种移动边缘计算(MEC)方案，以实现基于MPEGDASH(基于HTTP的动态自适应流媒体)的网络边缘辅助视频适配。与DASH客户端执行的传统OTT(Over-the-top)适配不同，移动网络边缘的MEC服务器可以通过其固有的无线网络信息服务(RNIS)功能捕获无线接入网络(RAN)状况，并使用这些知识向客户端提供指导，以便他们可以执行更智能的视频适配。为了支持这种MEC辅助的DASH视频改编，MEC服务器需要以当前网络吞吐量能够支持的质量本地缓存最流行的内容片段。为此，我们引入了一种二维用户体验质量(QOE)驱动的算法，用于基于内容上下文(例如，分段流行度)和网络上下文(例如，RAN下行链路吞吐量)来做出缓存/替换决策。我们在一个真实的基于LTE-A的网络测试床上部署了一个原型MEC服务器进行了实验。实验结果表明，与2种基准方案相比，我们提出的QOE驱动算法能够显著提高用户QOE。
In this paper, we present a Mobile Edge Computing (MEC) scheme for enabling network edge-assisted video adaptation based on MPEG-DASH (Dynamic Adaptive Streaming over HTTP). In contrast to the traditional over-the-top (OTT) adaptation performed by DASH clients, the MEC server at the mobile network edge can capture radio access network (RAN) conditions through its intrinsic Radio Network Information Service (RNIS) function, and use the knowledge to provide guidance to clients so that they can perform more intelligent video adaptation. In order to support such MEC-assisted DASH video adaptation, the MEC server needs to locally cache the most popular content segments at the qualities that can be supported by the current network throughput. Towards this end, we introduce a two-dimensional user Quality-of-Experience (QoE)-driven algorithm for making caching / replacement decisions based on both content context (e.g., segment popularity) and network context (e.g., RAN downlink throughput). We conducted experiments by deploying a prototype MEC server at a real LTE-A based network testbed. The results show that our QoE-driven algorithm is able to achieve significant improvement on user QoE over 2 benchmark schemes.